TY - JOUR
T1 - Multiscale analysis of vegetation surface fluxes
T2 - From seconds to years
AU - Katul, Gabriel
AU - Lai, Chun Ta
AU - Schäfer, Karina
AU - Vidakovic, Brani
AU - Albertson, John
AU - Ellsworth, David
AU - Oren, Ram
N1 - Funding Information:
The authors would like to thank Yavor Parashkevov and Cheng-I Hsieh for their assistance in the data collection and Judd Edburn for his overall help at the Duke Forest. This research was supported by the Department of Energy (DOE) Na- tional Institute for Global Environmental Change (NIGEC) through the NIGEC Southeast Regional Center at the University of Alabama in Tuscaloosa (DE-FC03-90ER61010) and the FACE-FACTS project, the National Science Foundation (NSF) Grants DMS-96-26159, EAR-99-03471, and BIR-95-12333 at Duke University. The M atlab programs can be obtained from the authors on request. The Duke Forest data sets can be accessed from http://152.16.58.129/facts-1/facts.html .
PY - 2001/11
Y1 - 2001/11
N2 - The variability in land surface heat (H), water vapor (LE), and CO2 (or net ecosystem exchange, NEE) fluxes was investigated at scales ranging from fractions of seconds to years using eddy-covariance flux measurements above a pine forest. Because these fluxes significantly vary at all these time scales and because large gaps in the record are unavoidable in such experiments, standard Fourier expansion methods for computing the spectral and cospectral statistical properties were not possible. Instead, orthonormal wavelet transformations (OWJ) are proposed and used. The OWJ are ideal at resolving process variability with respect to both scale and time and are able to isolate and remove the effects of missing data (or gaps) from spectral and cospectral calculations. Using the OWJ spectra, we demonstrated unique aspects in three appropriate ranges of time scales: turbulent time scales (fractions of seconds to minutes), meteorological time scales (hour to weeks), and seasonal to interannual time scales corresponding to climate and vegetation dynamics. We have shown that: (1) existing turbulence theories describe the short time scales well, (2) coupled physiological and transport models (e.g. CANVEG) reproduce the wavelet spectral characteristics of all three land surface fluxes for meteorological time scales, and (3) seasonal dynamics in vegetation physiology and structure inject strong correlations between land surface fluxes and forcing variables at monthly to seasonal time scales. The broad implications of this study center on the possibility of developing low-dimensional models of land surface water, energy, and carbon exchange. If the bulk of the flux variability is dominated by a narrow band or bands of modes, and these modes "resonate" with key state and forcing variables, then low-dimensional models may relate these forcing and state variables to NEE and LE.
AB - The variability in land surface heat (H), water vapor (LE), and CO2 (or net ecosystem exchange, NEE) fluxes was investigated at scales ranging from fractions of seconds to years using eddy-covariance flux measurements above a pine forest. Because these fluxes significantly vary at all these time scales and because large gaps in the record are unavoidable in such experiments, standard Fourier expansion methods for computing the spectral and cospectral statistical properties were not possible. Instead, orthonormal wavelet transformations (OWJ) are proposed and used. The OWJ are ideal at resolving process variability with respect to both scale and time and are able to isolate and remove the effects of missing data (or gaps) from spectral and cospectral calculations. Using the OWJ spectra, we demonstrated unique aspects in three appropriate ranges of time scales: turbulent time scales (fractions of seconds to minutes), meteorological time scales (hour to weeks), and seasonal to interannual time scales corresponding to climate and vegetation dynamics. We have shown that: (1) existing turbulence theories describe the short time scales well, (2) coupled physiological and transport models (e.g. CANVEG) reproduce the wavelet spectral characteristics of all three land surface fluxes for meteorological time scales, and (3) seasonal dynamics in vegetation physiology and structure inject strong correlations between land surface fluxes and forcing variables at monthly to seasonal time scales. The broad implications of this study center on the possibility of developing low-dimensional models of land surface water, energy, and carbon exchange. If the bulk of the flux variability is dominated by a narrow band or bands of modes, and these modes "resonate" with key state and forcing variables, then low-dimensional models may relate these forcing and state variables to NEE and LE.
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U2 - 10.1016/S0309-1708(01)00029-X
DO - 10.1016/S0309-1708(01)00029-X
M3 - Article
AN - SCOPUS:0035518859
SN - 0309-1708
VL - 24
SP - 1119
EP - 1132
JO - Advances in Water Resources
JF - Advances in Water Resources
IS - 9-10
ER -